Since the release of the Met Office Subset recently, I have been looking further at the data trying to evaluate what exactly is contained therein. One of the checks that one would like to do – determining how the global gridded data is calculated – is not really possible. The data set is self-admittedly incomplete and, anyway, a list of which stations are used and which aren’t is not provided. However, I decided to look at the grid cells information of the provided stations anyway to see what was going on.

Using another fairly extensive file of station information which I already possessed, ghcnd-stations.txt (which I believe to be downloaded from the previous incarnation of ClimateAudit.org), I did some checking of Met station information against the ghcn file. Using only those that I could easily match up in the two data sets, I found differences in coordinates and elevations of a number of stations. Although the heights (altitudes) need to be looked into further, because some of the differences can be quite large, the grid squares of most of the numerically different coordinates seemed to be unaffected by those differences. Except …

I have mentioned before that for some unknown reason, Met and Cru prefer to do the opposite of what one might normally expect for coding longitude values. East of Greenwich, their longitudes are negative and those west are positive – not what one would expect for drawing maps and not what one might generally find in other global reference venues. Unfortunately, this seems to have also caused some confusion for the Met Office.

From the Met data subset, the meta-information describing the following stations in the South Pacific was:

id

name

country

lat

long

height

1596

916500

ROTUMA

FIJI

-12.5

-177.1

62

1599

916830

NAUSORI A

FIJI

-18.1

-178.6

6

1604

917880

NUKU’ALOFA

TONGA

-21.1

-175.1

2

1595

916430

FUNAFUTI

TUVALU

-8.5

179.1

1

1597

916520

UDU POINT

FIJI

-16.1

180

62

1598

916800

NADI A

FIJI

-17.8

177.5

16

1600

916990

ONO-I-LAU

FIJI

-20.7

178.7

27

1601

917530

HIHIFO

WALLIS ISL.

-13.2

176.2

12

I plotted the locations in R (re-centering at the dateline – longitudes are measured from that coordinate). Grid cell boundaries are given in green. The graph on the left is the result:

The graph on the right is based on the coordinates gleaned from Wikipedia (yeah, I know…, but I trusted them anyway). The most obvious problem is that Nadi Airport from Fiji seems to have been relocated into the open ocean hundreds of kilometers from where a plane could safely land. But that is not the only error. Each of the four sites printed in blue on the right had the wrong sign for the longitude in the data. The net effect is that all four are NOT in the correct grid cell.

Is this important? I don’t know since we are not informed as to what is used in the calculation of the gridded data.

Could it have an effect on the global land series? Who knows? The southern portion of the tropical latitudes with wide ocean expanses and the absence of stations in a major part of central Africa is represented by relatively fewer grid cells and a sparser number of stations. As well, these latitude bands have a higher weight due to a larger area than the bands nearer the poles.

Either way, a little quality control would be a good first step toward producing some confidence in the whole process.

<blockquote>Ono-i-Lau is a volcanic and coral island in Fiji’s Lau archipelago.

One of the southernmost of the Lau Islands, it is located at 20.80° South and 178.75° East, and occupies an area of 7.9 square kilometers. It has a maximum elevation of 113 meters. It is 90 kilometers southsouthwest of Vatoa, the nearest island.</blockquote>

while the upper right corner on the same page gave the coordinates as 20°39′S, 178°44′W. I went with the text (confirmation bias? 😉 ).

No, confidence does not seem to go hand inn hand with what we have been looking at. I mentioned that the many altitudes seemed drastically out of whack with the comparison set, but since I had no reason to determine which of them might be wrong, I did not pursue it further at this time..

Nice stuff on your blog. I think you are correct in that fact that the South Pacific plays an inordinate role in the estimation of tropical global temperature. As a start, it would be real nice to have an actual list of the stations they use for the gridded data. With that in hand it would be easier to determine the adjustments implemented by CRU and the effect of those adjustments.

Google Earth shows NANDI located correctly using the coordinates above.
UNDU POINT is incorrect if 180 is considered positive, but correct if considered negative. At least close enough for government work.

Ahhh. The dangers of relying on Wikipedia. In the text they put ONO-I-LAU in the wrong hemisphere. They have it correct in the upper right corner coordinate reading.

I used the upper right corner for Ono-I-Lau when doing the right hand graph. Interestingly, I hadn’t noticed that the text was backwards. After reading your comment, I checked for it again at a different website for their airport:

Nandi Airport is west of the Nausori Airport when I used Google maps so it was obvious that that was incorrect in Met’s database.

Thanks for the links, They appear to be more useable than the ghcnd-stations.txt file. In that file, it wasn’t clear what the format of some of the station numbers was so I ignored part of the file when I was matching stations.

I’ve made up a Google map with all eight locations – the relative positions do not seem to agree closely to either of your plots: Some of the Met Office data indeed seems to have flipped signs, but so do some of your “other sources”. There seem to be problems with the latitudes as well: Rotuma comes out in Google as being much further north than any of the others, and they locate Udu Point at about the same latitude as Nadi and Nausori.

Sorry I am a Google Maps newbie and have no idea how to show a lat/long grid or point coordinates on their map.

“However *sigh* this led me to examine the detection of ‘non-standard longitudes’ – a
small section of code that converts PJ-style reversed longitudes, or 0-360 ones, to
regular -180 to +180 (E). This code is switched on by the presence of the
‘LongType’ flag in the LoadCTS call – the trouble is, THAT FLAG IS NEVER SET BY
ANOMDTB. There is a declaration ‘integer :: QLongType’ but that is never referred to
again. Just another thing I cannot understand, and another reason why this should all
have been rewritten from scratch a year ago!”

(continued in file)

Of course, those with the wrong sign or wrong number were not fixed correctly, but the odd longitudes (-180 to +180) don’t appear to have occurred in all stations in the source data that CRU actually used.

It appears that CRU and the Met should have known about the issues involved and fixed them properly long ago. Instead, they seem to have ignored the possible problems that could (and would given half a chance) occur due to poor programming and data base setup.